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Mixing reliability with Celery for delicious async tasks
Learn how to mix reliability with Celery for asynchronous tasks by understanding task signatures, visibility timeout, and retry mechanisms to ensure task correctness and efficient task management.
- Celery is an asynchronous task queue that can produce unexpected results if not configured correctly.
- Task signatures can change, which can cause tasks to be dropped or re-delivered unnecessarily.
- Task Accelerate False is the default, which means that tasks are intentionally dropped on worker failure.
- Task loss risks occur when the web process and broker communicate, and can be mitigated by using retry mechanisms.
- Visibility timeout is a trade-off between fast re-delivery and long task support.
- Celery’s default visibility timeout is 30 minutes, but can be customized.
- Task_accelerate True solves the problem of lost tasks, but may re-deliver tasks unnecessarily.
- Task loss can occur when the worker process dies due to out-of-memory errors or unexpected shutdowns.
- Using a retry mechanism with visibility timeout can help ensure tasks are re-delivered correctly.
- It’s important to handle task exceptions with the same diligence as 500 errors in Django.
- SQL databases can be used to store task metadata, allowing for easy tracking and recovery of tasks.
- Workflow-focused tools like Prefect, Temporal, and Airflow can be used for complex workflows.
- Celery’s retry mechanism can be triggered by visibility timeout, which can help ensure tasks are re-delivered correctly.
- It’s important to test and validate task code to ensure it’s safely retriable and doesn’t produce unexpected results.
- Task exceptions should be handled with the same diligence as 500 errors in Django, and task retries should be implemented to ensure tasks are re-delivered correctly.
- Celery’s re-delivery mechanism can be customized to suit specific requirements.
- Task latency can be managed by configuring the broker and worker to handle tasks efficiently.
- Visibility timeout can be used to balance fast re-delivery and long task support.
- Celery’s internal task payloads can change, which can cause tasks to be re-delivered unnecessarily.
- It’s important to test and validate task code to ensure it’s safely retriable and doesn’t produce unexpected results.
- Workflow-focused tools like Prefect, Temporal, and Airflow can be used for complex workflows.
- Celery’s retry mechanism can be triggered by visibility timeout, which can help ensure tasks are re-delivered correctly.